06/16/2026
What is RAG - and why does every serious healthcare AI Company talk about it?
Standard AI answers from memory (training data).
It can be months out of date, unverified, and confidently wrong. In healthcare, that's dangerous.
A 2026 Mayo Clinic study found that standard AI answered complex clinical questions correctly less than 40% of the time.
For a hospital, that's not a stat. That's a liability.
RAG fixes this.
RAG (Retrieval-Augmented Generation) changes the architecture entirely. Instead of generating answers from training data alone, RAG:
โRetrieves relevant chunks from your trusted data sources
โGrounds the AI response in that context
โCites the source -
so clinicians can verify It reduces hallucinations by up to 90% compared to standard LLMs.
The question for healthcare leaders is no longer "should we use AI?" It's "does our AI retrieve before it generates?"
